Aug 2026· Asia-Pacific Workshop on Networking· 0 citations· 29 references
Computer Science
TL;DR
ProLet is a load balancing scheme that enables proactive probing and reroutes elephant flows at flowlet granularity in lossless RDMA networks and reduces average and tail flow completion time slowdowns by 69% and 79%, respectively, compared to state-of-the-art load balancing schemes.
Abstract
To achieve high-throughput and low-latency Remote Direct Memory Access (RDMA) communication in data center networks, load balancing is critical for preventing congestion and ensuring that traffic is efficiently distributed across available network paths. However, existing schemes may not effectively detect rerouting opportunities in continuous RDMA packet streams and may degrade in-order delivery, limiting their applicability to RDMA traffic. To address these limitations, we propose ProLet, a load balancing scheme that enables proactive probing and reroutes elephant flows at flowlet granularity in lossless RDMA networks. ProLet dynamically fine-tunes per-destination top-of-rack timeouts and enables effective in-network flowlet identification based on real-time network conditions. Meanwhile, it leverages lightweight mice flows as proactive probes to maintain network-wide congestion awareness. This allows ProLet to reroute elephant flows before congestion accumulates, mitigating the persistent queue buildup inherent in subflow-based schemes. Extensive numerical evaluations demonstrate that ProLet reduces average and tail flow completion time slowdowns by 69% and 79%, respectively, compared to state-of-the-art load balancing schemes.
ProFlow leverages distributed telemetry signals and offline-trained reinforcement learning to identify precursor congestion conditions and proactively reroute protected flows before throughput degradation occurs, demonstrating the effectiveness of anticipatory congestion management.
Sourya Saha, Md. Nurul Absur, Saptarshi Debroy· IEEE Conference on Local Com...· 0 citations
Remote Direct Memory Access (RDMA) is widely adopted for high-performance datacenter workloads, but its strict ordering requirement conflicts with multipath transport in lossy networks. RDMA Network Interface Cards (RNICs) may interpret Out-of-Order (OOO) arrivals caused by diverse path latencies as packet loss. This triggers unnecessary retransmissions, severely degrading goodput collapse and inflating Flow Completion Time (FCT). We present PSN-PATH, a novel RDMA protocol to distinguish packet loss from OOO and avoid unnecessary retransmission, improving goodput and FCT of multi-path RDMA in lossy networks. PSN-PATH maps Packet Sequence Numbers (PSN) to network paths, enabling the receiver to verify packet continuity within each mapped path and distinguish real losses from OOO arrivals. PSN-PATH only retransmits lost packets and redirects traffic away from degraded paths. We implement PSN-PATH on Xilinx Alveo U50 FPGA using Vitis HLS and validate it via extensive simulation experiments. Experimental results demonstrate that PSN-PATH significantly outperforms existing solutions, reducing FCT by 95.81%, enhancing goodput by 5.11×, and reducing retransmissions by over 99% under high-load, lossy conditions.
Zhexiong Li, Shugui Wei, Puyu Zhao et al.· Conference on Applications,...· 0 citations
As RDMA becomes increasingly tolerant to out-of-order delivery, fine-grained packet-level multipathing is emerging as a practical design for datacenter fabrics. Packet spraying and related schemes improve load distribution for large flows, but they also force RDMA flows onto multiple paths whose conditions can differ at short timescales due to randomized traffic placement. For short flows, even one packet sent on a temporarily slower path can delay the entire flow. As a result, fine-grained load balancing can hurt, rather than help, small multi-packet flows. We present PIN, a lightweight wrapper that layers on top of any existing fine-grained RDMA load balancer. PIN applies less multipathing to short flows, which benefit from it least: it pins short flows to one path for their lifetime and leaves larger flows to the baseline mechanism. The design is simple, compositional, and requires only a size threshold. We show analytically that practical thresholds preserve overall load-balance fairness while reducing short-flow exposure to temporarily slower paths. Large-scale simulations across a variety of workloads show that PIN consistently improves both mean and tail completion time for short flows across multiple RDMA load-balancing baselines.
Jichun Wu, Ran Shu, A. Moore et al.· Asia-Pacific Workshop on Net...· 0 citations
Initial evaluations demonstrate that PFC-S can reduce the average flow completion time and effectively prevent congestion spreading, and experimental results show that PFC-S provides better protection for victim flows compared to standard PFC, BFC, and HPCC methods.
Weimin Gao, Jiawei Huang, Qile Wang et al.· Journal of High Speed Networ...· 0 citations
Datacenter performance is often limited by network-centric congestion controls relying on low-level metrics (e.g., packet loss, latency) that misinterpret applications needs. This work argues that applications should participate in congestion control decisions and introduces the starvation ratio (SR), a metric that detects when applications are truly limited by the network. Experimental evaluations within an 11-flow bottleneck scenario on a Linux-based prototype show that asynchronous applications can absorb network variations within a newly identified “silence zone” without degradation, proving conventional controls are overly restrictive. By deploying proactive and reactive mechanisms, our approach consistently reduces Flow Completion Time (FCT) for network-sensitive workloads. Notably, the proactive configuration eliminates micro-recovery delays, keeping the starvation ratio close to zero and reinforcing the baseline protocol through stable congestion window regulation. We conclude that shifting to application-driven signaling aligns network transmission with the receiver’s processing pace, preventing computational underutilization.
Anderson Henrique da Silva Marcondes, Enzo B. Boscatto, Guilherme Piêgas Koslovski· Anais do LIII Seminário Inte...· 0 citations
Driven by the requirements of machine learning, cloud storage, and other network-intensive applications, remote direct memory access (RDMA) has been widely adopted in high-speed networks and is gradually being applied to geographically distributed datacenters. However, in cross-datacenter scenarios, long control loop latency and mixed traffic prevent existing RDMA congestion control schemes from perceiving and reacting to congestion in a timely and fair manner; this can lead to severe performance degradation and unfairness. To address these issues, we propose cdcPIM, a proactive congestion control scheme extended from datacenter parallel iterative matching (dcPIM) for cross-datacenter networks, which restructures the end-to-end control loop by introducing switch-coordinated control points, effectively transforming long-haul, RTT-bound feedback into localized control. Specifically, cdcPIM deploys a local control point by moving the token generation from the receiver to the sender side cross-datacenter switch, constraining the congestion control loop for inter-datacenter traffic within a single datacenter. Furthermore, cdcPIM introduces a remote control point to perform admission control for inter-datacenter traffic entering the receiver’s datacenter, thus avoiding intra-datacenter congestion caused by traffic bursts. Simulations demonstrate that when cdcPIM manages inter-datacenter traffic while cooperating with datacenter quantized congestion notification (DCQCN) for intra-datacenter traffic, long-haul congestion is effectively mitigated. Under mixed cross-datacenter workloads, DCQCN + cdcPIM reduces the overall average flow completion time (FCT) slowdown by up to 25.7% and the P99 FCT slowdown of intra-DC flows by up to 65.0% compared with the baseline scheme Themis.
Wenqiang Deng, Junyan Chen, Xuefeng Huang et al.· Journal of King Saud Univers...· 0 citations
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